Nicolas Roux

Serotoninergic Fine-Tuning of the Excitation–Inhibition Balance in Rat Visual Cortical Networks

Fundamental brain functions depend on a balance between excitation (E) and inhibition (I) that is highly adjusted to a 20-80% set point in layer 5 pyramidal neurons (L5PNs) of rat visual cortex. Dysregulations of both the E-I balance and the serotonergic system in neocortical networks lead to serious neuronal diseases including depression, schizophrenia, and epilepsy. However, no link between the activation of neuronal 5-hydroxytryptamine receptors (5-HTRs) and the cortical E-I balance has yet been reported. Here we used a combination of patch-clamp recordings of composite stimulus-locked responses in L5PN following local electrical stimulations in either layer 2/3 or 6, simultaneous measurement of excitatory and inhibitory conductance dynamics, together with selective pharmacological targeting and single-cell reverse transcriptase-polymerase chain reaction. We show that cortical serotonin shifts the E-I balance in favor of more E and we reveal fine and differential modulations of the E-I balance between 5-HTR subtypes, in relation to whether layer 2/3 or 6 was stimulated and in concordance with the specific expression pattern of these subtypes in pyramidal cells and deep interneurons. This first evidence for the functional segregation of 5-HTR subtypes sheds new light on their coherent functioning in polysynaptic sensory circuits.

Homeostatic control of the excitation-inhibition balance in cortical layer 5 pyramidal neurons

Homeostatic regulation in the brain is thought to be achieved through a control of the synaptic strength by close interactions between excitation and inhibition in cortical circuits. We recorded in a layer 5 pyramidal neuron of rat cortex the composite response to an electrical stimulation of various layers (2–3, 4 or 6). Decomposition of the global conductance change in its excitatory and inhibitory components permits a direct measurement of excitation–inhibition (E‐I) balance. Whatever the stimulated layer was, afferent inputs led to a conductance change consisting of 20% excitation and 80% inhibition. Changing synaptic strengths in cortical networks by using a high‐frequency of stimulation (HFS) protocol or a low‐frequency of stimulation (LFS) protocol (classically used to induce long‐term potentiation or long‐term depression at the synaptic level) were checked in order to disrupt this balance. Application of HFS protocols in layers 2–3, 4 or 6, or of LFS protocols in layer 4 induced, respectively, long‐term paralleled increases or long‐term paralleled decreases in E and I which did not change the E‐I balance. LFS protocols in layers 2–3 or 6 decreased E but not I and disrupted the balance. It is proposed that regulatory mechanisms might be mainly sustained by recurrent connectivity between excitatory and inhibitory neuronal circuits and by modulation of shunting GABAA inhibition in the layer 5 pyramidal neuron.

Estimation of the degree of polarization in active coherent imagery by using the natural representation.

We address the problem of degree of polarization estimation in polarization diversity images. We consider active imaging techniques with laser illumination, which have the appealing feature of revealing contrasts that do not appear in conventional intensity images. These techniques provide two images of the same scene that are perturbed with speckle noise. Because of the presence of nonhomogeneity in the reflected intensity, it can be preferable to perform image analysis of the orthogonal-state contrast image, which is a measure of the degree of polarization of the reflected light when the coherency matrix is diagonal. It has been shown that a simple nonlinear transformation of this orthogonal-state contrast image leads to an image perturbed with additive symmetrical noise on which simple and efficient estimation and detection techniques can be applied. We propose to precisely analyze estimation properties of the degree of polarization using this natural representation. In particular, we determine the Cramer-Rao bound of the polarization degree estimation and the variance of the proposed estimator, and we study the estimators efficiency as a function of the speckle order for different measurement strategies.

Involvement of NR2A-or NR2B-containing N-methyl-D-aspartate receptors in the potentiation of cortical layer 5 pyramidal neurone inputs depends on the developmental stage

In the cortex, N‐methyl‐d‐aspartate receptors (NMDARs) play a critical role in the control of synaptic plasticity processes. We have previously shown in rat visual cortex that the application of a high‐frequency stimulation (HFS) protocol used to induce long‐term potentiation in layer 2/3 leads to a parallel potentiation of excitatory and inhibitory inputs received by cortical layer 5 pyramidal neurones without changing the excitation/inhibition balance of the pyramidal neurone, indicating a homeostatic control of this parameter. We show here that the blockade of NMDARs of the neuronal network prevents the potentiation of excitatory and inhibitory inputs, and this result leaves open to question the role of the NMDAR isoform involved in the induction of long‐term potentiation, which is actually being strongly debated. In postnatal day (P)18–23 rat cortical slices, the blockade of synaptic NR2B‐containing NMDARs prevents the induction of the potentiation induced by the HFS protocol, whereas the blockade of NR2A‐containing NMDARs reduced the potentiation itself. In P29–P32 cortical slices, the specific activation of NR2A‐containing receptors fully ensures the potentiation of excitatory and inhibitory inputs. These results constitute the first report of a functional shift in subunit composition of NMDARs during the critical period (P12–P36), which explains the relative contribution of both NR2B‐ and NR2A‐containing NMDARs in synaptic plasticity processes. These effects of the HFS protocol are mediated by the activation of synaptic NMDARs but our results also indicate that the homeostatic control of the excitation/inhibition balance is independent of NMDAR activation and is due to specialized recurrent interactions between excitatory and inhibitory networks.

Performance parameters for detection in low-flux coherent images

We analyze the optimization of low-flux coherent active imagery systems for target detection. We demonstrate that, unlike the Fisher ratio, the Bhattacharyya distance is an efficient figure of merit when one uses detection algorithms based on the generalized likelihood ratio test for realistic situations when the target and the background mean values are unknown. For example, we show that detection capabilities can be better if the pulse energy is divided into four shots, whereas using more than ten shots does not significantly improve the results.

Some practical issues in anomaly detection and exploitation of regions of interest in hyperspectral images

We address method of detection of anomalies in hyperspectral images that consists in performing the detection when the spectral signatures of the targets are unknown. We show that, in real hyperspectral images, use of the full spectral resolution may not be necessary for detection but that the correlation properties of spectral fluctuations have to be taken into account in the design of the detection algorithm. Anomaly detectors are useful for detecting regions of interest (ROIs), but, as they are prone to false alarms, one must analyze the ROIs obtained further to decide whether they correspond to real targets. We propose a method of exploitation of these ROIs that consists in generating a single image in which the contrast of the ROI is optimized.